How Can Data Science Improve UX Design?

Web design has already changed a great deal, primarily with the development of UX design. And now, as data science advances into the niche, we can expect it to change even more. As teams seek to hit that fine note which will make a website or app ideally user-centric, pairing UX designers and researchers with data analysts could eliminate plenty of guesswork and fine-tune both the creative process and its outcome. Here is how data science can help bring UX design to a whole new level.

Finding what resonates with the target audience

If you’re designing a completely new product – something beyond an existing category in the current market – you could be led by the approach that the users don’t know what they want. You could say that you’ll take it upon yourself to show them what it is that they want through sublime design. That’s if you had in mind something that wasn’t on the table already…and if you’re especially keen on emulating Steve Job’s approach for better or worse.

But when you’re designing a website or a mobile app, you can bet that your users have a pretty clear idea of what they want, even though many of them may not be personally able to put it into words. Yes, they surely want seamless navigation – but what does that mean for the focus group that you’re designing for?

There are a ton of intricacies regarding the issue, and while plenty of professionals understand there’s no one-size-fits all-recipe, we still haven’t found an approach that will help designers delve into their work with a deeper understanding. We have plenty of bits and pieces, but without robust data, we’re still largely relying on educated guesses and some fairly intangible principles.

No matter how fabulous a design seems or why you think it provides an ideal user experience, the point is that no designer, no matter how masterful of the craft, can predict what the users want. Plus, being familiar with your product and deeply invested in its success, a lot of objectivity is taken out of the work.

Of course, that’s why usability tests are vital to the entire process. But when it comes to the creative process, way before user testing, data could provide guidance throughout the whole way. With data-driven UX, it’s about having all the insights you need to minimize guesswork and not have to keep coming back to earlier phases of the process.

Now, there are plenty of data sources which give us insight into user preferences and the best UX design practices. Free tools – Google analytics, for one – provide a certain level of insight, but the true artfulness lies in being able to navigate all that information. It’s not about the data – but rather about compiling and analyzing robust data properly in order to find the problems which will need creative solutions.

Getting past the cookie-cutter approach

Assumptions are a major problem with the creative process of UX design. When you have an idea that something should work marvelously, it’s hard to shake that idea off, because you’re simply not thinking the way your users are. And that’s only normal. UX best practices and current trends also largely contribute to these assumptions, and designers need something to grab on to and move beyond them.

Otherwise, you end up with a cookie-cutter website that doesn’t really resonate with the audience although it’s crafted according to all the rules and best practices. Of course, there are longstanding UX principles but the problem arises when principles become rules you follow to the letter, and you stop approaching the same principle form another (equally viable) angle. Understanding this fact alone largely separates successful web design agencies from mediocre ones. If you take the time to sift through their profiles and portfolios, you’ll be able to find all kinds of different takes on UX solutions, which ultimately makes for authentic and impressive websites.

It’s interesting to note that of all things, data science can help guide designers in a more creative direction, tailoring the user experience specifically to each audience. Data science is all too often associated with the lack of innovation, but in this case, it’s just the thing designers need to break away from the standardized process and craft products which resonate with the target audience ideally.

Backing up daring design hypotheses

We’ve just talked about how data, contrary to popular belief, is much more likely to encourage creative design than to inhibit it. When UX designers, researchers, and data scientists work together, the outcome may not only provide a highly personalized and optimized user experience, but help break the mould as well.

Once again, it’s about how the data is interpreted and used. If you focus on immediate demands such as improving conversion rates, you can always refer to the data to backup your decision to stick to the tried and tested methods which should at least put a Band-Aid over the problem. But if the teams work together to truly gain insight into the meaning of all the data, designers could have a whole new field of opportunity opened up to them. You’ll have a lot more to work with to get the gears in motion, and it could bring you to daring, innovative proposals. In that case, the data will be there to help you convince the stakeholders and clients.

So when you want to completely redesign something, you’ll have user tests, site analytics, and various surveys (customer surveys if you’re redesigning checkout on an e-commerce website, for example) to help you make an informed decision.

The Takeaway

In summation, we can say that access to data from the start helps UX designers:

find the necessary direction to make the most of their creative process

focus on very specific problems they might not have otherwise anticipated and use the knowledge they have of the target audience to explore the most viable solutions

discover new patterns, trends, and solutions, and find opportunities for creative solutions within specific user segments.

The data science team will also help designers ensure they’re on the right track during certain phases of the work, taking out much of the guesswork prior to usability testing.

Lastly, data enhances UX design by adding objectivity and it could even encourage innovation.

Getting the design and data science team to work closely together would make for a truly holistic approach to UX design – one that will help make giant strides.

About the Author

Nina Ritz is a technical researcher & writer at DesignRush, a B2B marketplace connecting brands with agencies. She loves to share her experiences and meaningful content that educates and inspires people. Her main interests are web design and marketing. In her free time, when she’s away from the computer, she likes to do yoga and ride a bike.

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